- 📁 docs/
- 📁 examples/
- 📁 references/
- 📄 .gitignore
- 📄 AGENTS.md
- 📄 LICENSE
adversarial-review
Adversarial AI code/plan review. Codex reviews, Claude fixes, iterative loop until approved. Auto-detects plan/code/code-vs-plan mode.
Adversarial AI code/plan review. Codex reviews, Claude fixes, iterative loop until approved. Auto-detects plan/code/code-vs-plan mode.
ALWAYS use when writing code importing \"@clack/prompts\". Consult for debugging, best practices, or modifying @clack/prompts, clack/prompts, clack prompts, clack.
VCC (View-oriented Conversation Compiler) documentation. Compile Claude Code JSONL logs into adaptive views.
Give your AI agents something more useful than a prompt. Velocity through clarity.
- 适合获取最新 AI / 大模型 / 生成式 AI 新闻、热点和来源列表。
Manage persistent coding sessions across Claude Code, Codex, Gemini, and Cursor engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, or switching models/tools at runtime. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "switch model", "multi-agent", "coding session", "session inbox", "cursor agent".
Open the Claude Code Organizer dashboard — view and manage all memories, skills, MCP servers, hooks, and configs across scopes
DashClaw platform expert for integration, troubleshooting, and governance. Use when working with DashClaw APIs/SDKs: instrumenting agents, action recording, guard/policy checks, SSE real-time events, org/workspace context, auth headers (x-api-key), errors (401/403/429/503), building API routes, generating SDK/client methods, bootstrapping agent data, configuring evaluations/scorers, prompt templates/versioning, feedback capture, compliance exports, drift monitoring, learning analytics/velocity, scoring profiles, risk templates, CLI approval channel, terminal approvals, dashclaw approve, dashclaw approvals, dashclaw deny, Claude Code hooks, PreToolUse, PostToolUse, governed tool calls, DASHCLAW_HOOK_MODE, terminal governance.
Claude Code Source - Buildable Research Fork. Reverse-engineered build system, runnable with Bun.
OS-level desktop automation tool server. 42 tools for controlling any application on Windows, macOS, and Linux. Model-agnostic — works with any AI that can do function calling via REST or MCP (Claude, GPT, Gemini, Llama, Mistral, or plain HTTP). No built-in LLM in serve/mcp mode. You are the brain. ClawdCursor is the hands.
Mission control dashboard for OpenClaw - real-time session monitoring, LLM usage tracking, cost intelligence, and system vitals. View all your AI agents in one place.
Example Claude skill
skill-sample/ ├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps) ├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill) ├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial) ├─ scripts/ │ └─ example-run.py ✅ Runnable example script for quick verification ├─ assets/ │ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style │ └─ example-template.tex 🧩 Templates: quickly generate standardized output └─ references/ 🧩 Knowledge base: methods / guides / best practices ├─ example-ref-structure.md 🧩 Structure reference ├─ example-ref-analysis.md 🧩 Analysis reference └─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs Anthropic docs: https://agentskills.io/home
├─ ⭐ Required: YAML Frontmatter (must be at top) │ ├─ ⭐ name : unique skill name, follow naming convention │ └─ ⭐ description : include trigger keywords for matching │ ├─ ✅ Optional: Frontmatter extension fields │ ├─ ✅ license : license identifier │ ├─ ✅ compatibility : runtime constraints when needed │ ├─ ✅ metadata : key-value fields (author/version/source_url...) │ └─ 🧩 allowed-tools : tool whitelist (experimental) │ └─ ✅ Recommended: Markdown body (progressive disclosure) ├─ ✅ Overview / Purpose ├─ ✅ When to use ├─ ✅ Step-by-step ├─ ✅ Inputs / Outputs ├─ ✅ Examples ├─ 🧩 Files & References ├─ 🧩 Edge cases ├─ 🧩 Troubleshooting └─ 🧩 Safety notes
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
Use these three together:
Note: file size for all methods should be within 10MB.
Typical paths (may vary by local setup):
One SKILL.md can usually be reused across tools.
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
Most common reasons:
We try to avoid that. Use ranking + comments to surface better skills: